Learning Path: R: Master R Data Analysis and Visualization

AulaGEO Academy

Training

Online

up to £ 100

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Description

  • Type

    Training

  • Methodology

    Online

  • Class hours

    12h

  • Start date

    Different dates available

"R is one of the most comprehensible statistical tool for managing and manipulating data. With the ever increasing number of data, there is a very high demand of professionals who have got skills to analyze these data. If you're looking forward to becoming an expert data analyst, then go for this Learning Path.Packt’s Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.Let’s take a quick look at your learning journey! This Learning Path begins with familiarizing you with the programming and statistics aspects of R. You will learn how CRAN works and why to use it. Acquire the ability to conduct data analysis in practical contexts with R, using core language packages and tools. Moving ahead, the Learning Path will gradually take you through creating interactive maps using the googleVis package. By the end of this Learning Path, you will be equipped with all data analysis and visualization techniques and build a strong foundation for moving into data scienceWe have combined the best authors: Dr. Samik Sen is a theoretical physicist and loves thinking about hard problems. After his PH.D. in developing computational methods to solve problems for which no solutions existed, he began thinking about how to tackle math problems while lecturing.

Facilities

Location

Start date

Online

Start date

Different dates availableEnrolment now open

About this course

"Import and export data in various formats in RPerform advanced statistical data analysisVisualize your data on Google or Open Street mapsCreate simple and quick visualizations using the basic graphic tools in RImplement interactive visualizations using ggplot2.Add elements, text, animation, and colors to your plot to make sense of dataMaster network, radial, and coxcomb plots"

This Learning Path is aimed at aspiring or professional statisticians, data analysts, or data scientists who want to analyze and visualize data for gaining deeper insights of it.

"Basic programming knowledge of RBasic knowledge of Math and Statistics"

"-100% online -Access to the course for life -30 days warranty money back -Available from desktop or mobile app -Can begin and finish the course any time -Can repeat the course any times"

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Reviews

This centre's achievements

2020

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 3 years

Subjects

  • Data analysis
  • Programming
  • spatial
  • Spatial Distribution
  • Spatial points
  • Spatial analysis
  • Spatial Data
  • R
  • R Data
  • Datanalysis
  • Data Visualization
  • R Studio
  • Data
  • Raster data
  • Raster
  • Raster format
  • Vector
  • Vector data
  • Multivariate data
  • Plotting

Course programme

"Speaking ‘R’ - The Language of Data Science
The Course Overview
What Is R?
Getting and Setting Up R/Rstudio
Using RStudio
Packages
A Lot Is the Same
Familiar Building Programming Blocks
Putting It All Together
Core R Types
Some Useful Operations
More Useful Operations
Titanic
Tennis
It's Mostly Cleaning Up
The Most Widely Used Statistical Package
Distributions
Time to Get Graphical
Plotting to Another Dimension
Facets
Test Your Knowledge
Learning Data Analysis with R
The Course Overview
Importing Data from Tables (read.table)
Downloading Open Data from FTP Sites
Fixed-Width Format
Importing with read.lines (The Last Resort)
Cleaning Your Data
Loading the Required Packages
Importing Vector Data (ESRI shp and GeoJSON)
Transforming from data.frame to SpatialPointsDataFrame
Understanding Projections
Basic time/dates formats
Introducing the Raster Format
Reading Raster Data in NetCDF
Mosaicking
Stacking to Include the Temporal Component
Exporting Data in Tables
Exporting Vector Data (ESRI shp File)
Exporting Rasters in Various Formats (GeoTIFF, ASCII Grids)
Exporting Data for WebGIS Systems (GeoJSON, KML)
Preparing the Dataset
Measuring Spread (Standard Deviation and Standard Distance)
Understanding Your Data with Plots
Plotting for Multivariate Data
Finding Outliers
Introduction
Re-Projecting Your Data
Intersection
Buffer and Distance
Union and Overlay
Introduction
Converting Vector/Table Data into Raster
Subsetting and Selection
Filtering
Raster Calculator
Plotting Basics
Adding Layers
Color Scale
Creating Multivariate Plots
Handling the Temporal Component
Introduction
Plotting Vector Data on Google Maps
Adding Layers
Plotting Raster Data on Google Maps
Using Leaflet to Plot on Open Street Maps
Introduction
Importing Data from the World Bank
Adding Geocoding Information
Concluding Remarks
Theoretical Background
Introduction
Intensity and Density
Spatial Distribution
Modelling
Theoretical Background
Data Preparation
K-Means Clustering
Optimal Number of Clusters
Hierarchical Clustering
Concluding
Theoretical Background
Reading Time-Series in R
Subsetting and Temporal Functions
Decomposition and Correlation
Forecasting
Theoretical Background
Data Preparation
Mapping with Deterministic Estimators
Analyzing Trend and Checking Normality
Variogram Analysis
Mapping with kriging
Theoretical Background
Dataset
Linear Regression
Regression Trees
Support Vector Machines
Test Your Knowledge
R Data Visualization - Basic Plots, Maps, and Pie Charts
The Course Overview"

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Learning Path: R: Master R Data Analysis and Visualization

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